transforms.py 文件源码

def __call__(self, x_mu):
        """

        Args:
            x_mu (FloatTensor/LongTensor or ndarray)

        Returns:
            x (FloatTensor or ndarray)

        """
        mu = self.qc - 1.
        if isinstance(x_mu, np.ndarray):
            x = ((x_mu) / mu) * 2 - 1.
            x = np.sign(x) * (np.exp(np.abs(x) * np.log1p(mu)) - 1.) / mu
        elif isinstance(x_mu, (torch.Tensor, torch.LongTensor)):
            if isinstance(x_mu, torch.LongTensor):
                x_mu = x_mu.float()
            mu = torch.FloatTensor([mu])
            x = ((x_mu) / mu) * 2 - 1.
            x = torch.sign(x) * (torch.exp(torch.abs(x) * torch.log1p(mu)) - 1.) / mu
        return x